A Maturity Model (MM) is essential for laboratories aiming to improve and compete globally. Despite being accredited for over 20 years, some laboratories lack evidence of system maturity necessary for international competitiveness. A higher maturity level indicates a robust quality management system, leading to improved efficiency, accuracy, and customer satisfaction, while also assuring stakeholders, such as customers and regulatory bodies, of the laboratory's commitment to continuous improvement. The MM is designed to assess the success of laboratory processes, management styles, and the development of quality management practices, based on the 4M model (Manpower, Method, Machine, Material). The MM was developed using Analytes Accurate Certain Score (AACS) for the ten most common tests and System Maturity Scores (SMS), which incorporate proficiency testing and audit scores over two accreditation cycles (six years). While the model identifies inefficiencies, it helps organizations pinpoint areas of improvement and devise strategies to enhance their operations. This study applied the MM to a commercial laboratory, ABC (anonymized), accredited since the early 1990s and having undergone eight assessment cycles. The laboratory was found to be at a “leading” maturity level with a score above 80%, although improvements are still needed. Key areas for improvement include: 1) **Manpower**: maintaining competent staff by adjusting management strategies, 2) **Method**: validating all in-house methods according to Analytical Laboratory Accreditation Criteria Committee (ALACC) guidelines, 3) **Machine**: applying good laboratory practices (GLP) for equipment sharing, especially for specific analytes, and 4) **Material**: ensuring metrologically traceable reference materials and proficiency testing for all analytes. These improvements will help the laboratory further enhance its global competitiveness.

Accuracy, reliability, defensibility, and timeliness are all aspects of laboratory quality. The outcomes must be error-free in order to produce high accuracy data. Valid methods and calibrated equipment are referred to as reliability. To dispute the laboratory results, all possible errors were identified and the measurement uncertainties were estimated. The certificate of analysis or report must be issued timely. Laboratories in Malaysia was referred to the ISO/IEC 17025 for accreditation purpose. There are three essential elements defined as the backbone of the laboratory quality system. Validate analytical methods, accreditation involving third part auditing and participation in proficiency testing (PT). For this study, PT data is used as a tool to assess laboratory quality management systems' competency. Even if their performance is satisfactory according to the PT provider's evaluation criteria, participants in PT can interpret their results to detect inaccuracies and possibilities for continuous improvement. One of the PT schemes from MyKIMIA Proficiency Testing Provider (PTP) selected for the case study, the overall percentage of satisfactory for the Food Analysis Scheme (FODAS) 1-20 Benzoic acid (BA) and Sorbic acid (SA) in cordial was in the range from 82% to 88%. Statistic performance evaluation was based on a calculation of Z score for Test 1, Test 2 and Test 4. The laboratories shall recalculate the Z score based on the PTP assigned value and fit for purpose standard deviation proficiency assessment (SDPA). Zeta score can be calculated to check the plausibility of the laboratory's measurement uncertainty estimate. The outlier data received that cause the poor performance include human errors, random errors, and systematic errors. Investigation on the errors is consistently based on four main factors: manpower, method, material, and machinery (4M).

This study delves into the evaluation of food laboratories through the implementation of a Maturity Model (MM) across two assessment cycles spanning a 6-year period. Accreditation, a critical aspect indicating a laboratory's adherence to established standards and competence in testing, is accompanied by the concept of maturity. Maturity, in this context, represents the level of development and effectiveness of a laboratory's quality management system, encapsulating operational efficiency, result accuracy, and customer satisfaction. Higher maturity levels not only optimize internal processes but also instill confidence in stakeholders, including customers and regulatory bodies. The MM, developed from Analytes Accurate Certain Score (AACS) and System Maturity Scores (SMS), assesses the development and implementation of quality management processes. The AACS focuses on the 4M framework: Manpower, Method, Machine, and Material, covering the ten most frequently tested analytes, while the SMS considers internal audit and external assessment findings, along with overall proficiency testing performance. Comparing commercial and government laboratories, both types demonstrated similar performance, falling within the "Emerging" level. However, the commercial sector exhibited a slightly higher Average MM score (67%) compared to government laboratories (64%), implying better accuracy. Lab S, a recently accredited commercial food lab, stood out with an exceptional MM score of 82%, achieving a "Leading" level with high SMS and AACS scores. Principal Component Analysis (PCA) served as an indicator for evaluating Proficiency Testing (PT) performance over time, while Monte Carlo Simulation (MCS) determined Measurement Uncertainty (MU) based on PT data. In the 2021 PT Scheme FODAS 1 for benzoic acid as the analyte, with 17 out of 19 participants achieved satisfactory results with MCS compared with only 13 who achieved satisfactory results previously. The study also explored MU assessment for various analytes, including caffeine, sorbic acid, calcium, chloramphenicol, and arsenic, using bottom-up, top-down, and MCS approaches. Consistent MU values were observed for benzoic acid and caffeine using both bottom up and top-down methods. In Sorbic Acid and Calcium analysis, the top-down approach resulted in higher MU, influenced by precision and trueness studies, while the MCS approach set maximum limits for participant comparison. In conclusion, this study emphasizes the importance of tailored approaches for accurate MU assessment, offering insights for laboratories to enhance measurement performance and quality assurance practices. The findings contribute valuable insights into general trends observed between government and commercial laboratories, Highlighting the need for continuous monitoring and improvement to maintain high-quality services and reliable results in both types of laboratories.